Influence of quinidine, fluvoxamine, and ketoconazole on the enantioselective pharmacokinetics of citalopram in rats
Bibliographic record
Abstract
Citalopram (CITA) is available as a racemic mixture or as (+)-(S)-CITA. In humans, CITA is metabolized to demethylcitalopram (DCITA) by CYP2C19, CYP2D6, and CYP3A and to didemethylcitalopram by CYP2D6. There are no data regarding the enzymes involved in CITA and DCITA metabolism in rats. The present study investigated the influence of CYP inhibitors on the enantioselective metabolism of CITA in rats. Male Wistar rats (n = 6) received a single dose of 20 mg x kg-1 CITA after pretreatment with 80 mg x kg-1 quinidine, 10 mg x kg-1 fluvoxamine, 50 mg x kg-1 ketoconazole, or vehicle (control). Blood samples were collected up to 20 h after CITA administration. The CITA and DCITA enantiomers were analyzed by LC-MS/MS using a Chiralcel OD-R column. The kinetic disposition of CITA was enantioselective in rats (AUCS/R ratio = 0.4). Coadministration with quinidine resulted in non-enantioselective inhibition of the metabolism of CITA. Coadministration with fluvoxamine or ketoconazole, however, inhibited only the metabolism of (+)-(S)-CITA, but not of (-)-(R)-CITA when the racemic drug was administered to rats.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".